Machine Learning Engineer jobs in United Kingdom

At Scottish Funding Council, we’re embarking on an exciting digital transformation to redefine how we use data to drive innovation and deliver exceptional value to our customers. Central to this journey is the creation of the Azure‑based data ecosystem, enabling us to unlock the full potential of our data through transformative and intelligent solutions.

Our Data Engineering team plays a pivotal role in this mission. We manage the entire data lifecycle—from integrating diverse data sources and optimizing storage and processing pipelines to delivering actionable insights—while ensuring compliance with company standards and data protection regulations.

As a Senior Data Engineer, you will be a technical leader within this dynamic team, driving innovation and engineering excellence. You’ll work closely with teams across the organisation, including Analytics and Cloud Engineering, to cultivate a data‑driven culture and lead initiatives that turn data into a powerful tool for transformation.

This role offers a unique opportunity to shape the future of post‑16 education in Scotland. By delivering innovative, data‑driven solutions, you will enable institutions and policymakers to make informed decisions, enhance learning outcomes, and create opportunities that empower students to thrive in an increasingly data‑centric world.

1. Translate business requirements into technical specifications, roadmaps and deliverable data solutions, including data streams, integrations, transformations, databases, data warehouses, and business intelligence, reporting and analytical platforms.
2. Define the data architecture framework, standards and principles, including modelling, metadata, security and data virtualisation.
3. Support the Head of Data Engineering to develop and enhance standards and policies/guidelines whilst driving adoption of standards.
4. Define data flows and data lineage, visualising which parts of the organization generate data, which require data to function, how data flows are managed, and how data changes in transition.
5. Provide technical guidance and advice to help in the design and development of data solutions for data modelling and warehousing, data integration, and analytics.
6. Provide direction and support to a team of data engineers and provide technical guidance on the data products.
7. Develop roadmaps for both product related DE work as well as overall data maturity roadmap.
8. Drive the design, building, and launching of new data models and data pipelines in production.
9. Perform peer reviews, audits, standards compliance checks and due diligence as required.
10. Report delivery progress and status to both internal and external stakeholders.

• Proven track record of designing, developing and delivering enterprise‑scale data products and solutions within the Microsoft Azure ecosystem.
• Advanced proficiency in SQL and modern data processing frameworks, coupled with strong programming skills in at least one language (Python preferred).
• Comprehensive expertise in data architecture, including dimensional modelling, data warehouse design patterns, and business intelligence solution architecture.
• Deep hands‑on technical knowledge acquired through extensive practical implementation experience.
• Exceptional analytical capabilities with proven ability to conduct comprehensive data profiling, source system analysis, and deliver actionable insights that drive business value.
• Demonstrated ability to translate complex technical concepts into clear, compelling narratives for diverse stakeholder audiences.
• Proven leadership experience in guiding and mentoring data engineering teams, fostering technical excellence and professional growth.
• Track record of identifying strategic data opportunities, initiating transformative projects, and driving technical direction from concept to successful delivery.
• Strong stakeholder management skills with the ability to influence and align technical solutions with organisational objectives.
• Outstanding interpersonal skills with demonstrated ability to engage effectively with technical teams and business stakeholders.
• Expertise in requirements gathering, solution design, and cross‑functional collaboration.
• Degree level education (SCQF level 9) or equivalent experience, ideally in a technical field such as Computer Science, Mathematics or Physics.

• Significant exposure to Azure utilising some of the following: Azure Synapse Analytics, Azure SQL, Azure Data Factory, Azure Data Lake, Azure DevOps and PowerBI.
• Azure Data Engineer Associate certification or higher OR Azure AI Engineer Associate certification or higher.
• Experience implementing solutions using Microsoft Fabric.